Publications by authors named "Gerald Loeb"

While interest in using wearable sensors to measure infant leg movement is increasing, attention should be paid to the characteristics of the sensors. Specifically, offset error in the measurement of gravitational acceleration () is common among commercially available sensors. In this brief report, we demonstrate how we measured the offset and other errors in three different off-the-shelf wearable sensors available to professionals and how they affected a threshold-based movement detection algorithm for the quantification of infant leg movement.

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When humans reach to visual targets, extremely rapid (∼90 ms) target-directed responses can be observed in task-relevant proximal muscles. Such express visuomotor responses are inflexibly locked in time and space to the target and have been proposed to reflect rapid visuomotor transformations conveyed subcortically via the tecto-reticulo-spinal pathway. Previously, we showed that express visuomotor responses are sensitive to explicit cue-driven information about the target, suggesting that the express pathway can be modulated by cortical signals affording contextual prestimulus expectations.

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Human manual dexterity relies critically on touch. Robotic and prosthetic hands are much less dexterous and make little use of the many tactile sensors available. We propose a framework modeled on the hierarchical sensorimotor controllers of the nervous system to link sensing to action in human-in-the-loop, haptically enabled, artificial hands.

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Recent research has illuminated the complexity and importance of the thalamocortical system but it has been difficult to identify what computational functions it performs. Meanwhile, deep-learning artificial neural networks (ANNs) based on bio-inspired models of purely cortical circuits have achieved surprising success solving sophisticated cognitive problems associated historically with human intelligence. Nevertheless, the limitations and shortcomings of artificial intelligence (AI) based on such ANNs are becoming increasingly clear.

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Humans and robots operating in unstructured environments both need to classify objects through haptic exploration and use them in various tasks, but currently they differ greatly in their strategies for acquiring such capabilities. This review explores nascent technologies that promise more convergence. A novel form of artificial intelligence classifies objects according to sensory percepts during active exploration and decides on efficient sequences of exploratory actions to identify objects.

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Humans can produce "express" (∼100 ms) arm muscle responses that are inflexibly locked in time and space to visual target presentations, consistent with subcortical visuomotor transformations via the tecto-reticulo-spinal pathway. These express visuomotor responses are sensitive to explicit cue-driven expectations, but it is unclear at what stage of sensory-to-motor transformation such modulation occurs. Here, we recorded electromyographic activity from shoulder muscles as participants reached toward one of four virtual targets whose physical location was partially predictable from a symbolic cue.

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Control of musculoskeletal systems depends on integration of voluntary commands and somatosensory feedback in the complex neural circuits of the spinal cord. It has been suggested that the various connectivity patterns that have been identified experimentally may result from the many transcriptional types that have been observed in spinal interneurons. We ask instead whether the muscle-specific details of observed connectivity patterns can arise as a consequence of Hebbian adaptation during early development, rather than being genetically ordained.

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Recent spinal cord literature abounds with descriptions of genetic preprogramming and the molecular control of circuit formation. In this paper, we explore to what extent circuit formation based on learning rather than preprogramming could explain the selective formation of the monosynaptic projections between muscle spindle primary afferents and homonymous motoneurons. We adjusted the initially randomized gains in the neural network according to a Hebbian plasticity rule while exercising the model system with spontaneous muscle activity patterns similar to those observed during early fetal development.

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Estimates of limb posture are critical for controlling robotic systems. This is generally accomplished with angle sensors at individual joints that simplify control but can complicate mechanical design and robustness. Limb posture should be derivable from each joint's actuator shaft angle but this is problematic for compliant tendon-driven systems where () motors are not placed at the joints and () nonlinear tendon stiffness decouples the relationship between motor and joint angles.

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Academic researchers concentrate on the scientific and technological feasibility of novel treatments. Investors and commercial partners, however, understand that success depends even more on strategies for regulatory approval, reimbursement, marketing, intellectual property protection and risk management. These considerations are critical for technologically complex and highly invasive treatments that entail substantial costs and risks in small and heterogeneous patient populations.

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Human cerebral cortex can produce visuomotor responses that are modulated by contextual and task-specific constraints. However, the distributed cortical network for visuomotor transformations limits the minimal response time of that pathway. Notably, humans can generate express visuomotor responses in arm muscles that are inflexibly tuned to the target location and occur 80-120 ms from stimulus presentation [stimulus-locked responses (SLRs)].

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Recurrent circuitry components are distributed widely within the brain, including both excitatory and inhibitory synaptic connections. Recurrent neuronal networks have potential stability problems, perhaps a predisposition to epilepsy. More generally, instability risks making internal representations of information unreliable.

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Data mining is a powerful tool to reduce costs and mitigate errors in the diagnostic analysis and repair of complex engineered system, but it has yet to be applied systematically to the most complex and socially expensive system - the human body. The currently available approaches of knowledge-based and pattern-based artificial intelligence are unsuited to the iterative and often subjective nature of clinician-patient interactions. Furthermore, current electronic health records generally have poor design and low quality for such data mining.

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Variability in muscle force is a hallmark of healthy and pathological human behavior. Predominant theories of sensorimotor control assume 'motor noise' leads to force variability and its 'signal dependence' (variability in muscle force whose amplitude increases with intensity of neural drive). Here, we demonstrate that the two proposed mechanisms for motor noise (i.

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Learning to use Muscles.

J Hum Kinet

January 2021

The human musculoskeletal system is highly complex mechanically. Its neural control must deal successfully with this complexity to perform the diverse, efficient, robust and usually graceful behaviors of which humans are capable. Most of those behaviors might be performed by many different subsets of its myriad possible states, so how does the nervous system decide which subset to use? One solution that has received much attention over the past 50 years would be for the nervous system to be fundamentally limited in the patterns of muscle activation that it can access, a concept known as muscle synergies or movement primitives.

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Background: Prosthetic restoration of reach and grasp function after a trans-humeral amputation requires control of multiple distal degrees of freedom in elbow, wrist and fingers. However, such a high level of amputation reduces the amount of available myoelectric and kinematic information from the residual limb.

Methods: To overcome these limits, we added contextual information about the target's location and orientation such as can now be extracted from gaze tracking by computer vision tools.

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Humans are able to generate target-directed visuomotor responses in less than 100 ms after stimulus onset. These "express" responses have been termed stimulus-locked responses (SLRs) and are proposed to be modulated by visuomotor transformations performed subcortically via the superior colliculus. Unfortunately, these responses have proven difficult to detect consistently across individuals.

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Congenital complete heart block (CCHB) is a life-threatening medical condition in the unborn fetus with insufficiently validated prenatal interventions. Maternal administration of medications aimed at decreasing the immune response in the fetus and beta-agonists intended to increase fetal cardiac output have shown only marginal benefits. Anti-inflammatory therapies cannot reverse CCHB, but may decrease myocarditis and improve heart function.

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Implantable electrical interfaces with the nervous system were first enabled by cardiac pacemaker technology over 50 years ago and have since diverged into almost all of the physiological functions controlled by the nervous system. There have been a few major clinical and commercial successes, many contentious claims, and some outright failures. These tend to be reviewed within each clinical subspecialty, obscuring the many commonalities of neural control, biophysics, interface materials, electronic technologies, and medical device regulation that they share.

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Background: Permanent cardiac pacemakers require invasive procedures with complications often related to long pacemaker leads. We are developing a percutaneous pacemaker for implantation of an entire pacing system into the pericardial space.

Methods: Percutaneous micropacemaker implantations were performed in 6 pigs (27.

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Advances in wearable sensor technology now allow us to quantify the number, type and kinematic characteristics of bouts of infant arm movement made across a full day in the natural environment. Our aim here was to determine whether the amount and kinematic characteristics of arm movements made across the day in the natural environment were related to developmental status in infants with typical development as they learned to reach for objects using their arms. We used wearable sensors to measure arm movement across days and months as infants developed arm reaching skills.

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We developed a wearable sensor algorithm to determine the number of arm movement bouts an infant produces across a full day in the natural environment. Full-day infant arm movement was recorded from 33 infants (22 infants with typical development and 11 infants at risk of atypical development) across multiple days and months by placing wearable sensors on each wrist. Twenty second sections of synchronized video data were used to compare the algorithm against visual observation as the gold standard for counting the number of arm movement bouts.

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We have developed and applied new methods to estimate the functional life of miniature, implantable, wireless electronic devices that rely on non-hermetic, adhesive encapsulants such as epoxy. A comb pattern board with a high density of interdigitated electrodes (IDE) could be used to detect incipient failure from water vapor condensation. Inductive coupling of an RF magnetic field was used to provide DC bias and to detect deterioration of an encapsulated comb pattern.

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Understanding of the musculoskeletal system has evolved from the collection of individual phenomena in highly selected experimental preparations under highly controlled and often unphysiological conditions. At the systems level, it is now possible to construct complete and reasonably accurate models of the kinetics and energetics of realistic muscles and to combine them to understand the dynamics of complete musculoskeletal systems performing natural behaviors. At the reductionist level, it is possible to relate most of the individual phenomena to the anatomical structures and biochemical processes that account for them.

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We have developed a percutaneously implantable and wireless microstimulator (NuStim) to exercise the pelvic floor muscles for the treatment of stress urinary incontinence. It produces a wide range of charge-regulated electrical stimulation pulses and trains of pulses using a simple electronic circuit that receives power and timing information from an externally generated RF magnetic field. The complete system was validated in vitro and in vivo in preclinical studies demonstrating that the NuStim can be successfully implanted into an effective, low threshold location, and the implant can be operated chronically to produce effective and well-tolerated contractions of skeletal muscle.

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